Paper Citation Record · LEDGER

Distribution Matching Distillation Meets Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 36 inbound Pith citation observations for arXiv:2511.13649.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2511.13649 v5

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T21:47:20.196175Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 36 of 36 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:17:25.986375Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

64 of 64 outbound references displayed

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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 98857ab8-643f-4a2a-bb46-09621a0577d4 · outbound

This paper cites Sd3.5.https : / / github.

Distribution Matching Distillation Meets Reinforcement Learning Sd3.5.https : / / github

Reference 1

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Observation 985470cc-614f-44f8-8a14-69f16da9e6e1 · outbound

This paper cites Towards Principled Methods for Training Generative Adversarial Networks.

Distribution Matching Distillation Meets Reinforcement Learning Towards Principled Methods for Training Generative Adversarial Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.761928Z

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Observation 5fa5e6bb-3635-4efb-ad53-a4e96cfa8da8 · outbound

This paper cites an unresolved cited work.

Distribution Matching Distillation Meets Reinforcement Learning Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.769160Z

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Observation b98c2429-a642-4df0-855a-0e5d24c54c8b · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

Distribution Matching Distillation Meets Reinforcement Learning Training Diffusion Models with Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.778313Z

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Observation 0fe8117d-f23f-4379-bda8-2f33ef3acc67 · outbound

This paper cites Flash diffusion: Accelerating any conditional diffusion model for few steps image generation.

Distribution Matching Distillation Meets Reinforcement Learning Flash diffusion: Accelerating any conditional diffusion model for few steps image generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.783757Z

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Observation 4a085be1-525c-4a7b-9f4f-d103b4eb370d · outbound

This paper cites pi-flow: Policy-based few- step generation via imitation distillation.arXiv preprint arXiv:2510.14974, 2025.

Distribution Matching Distillation Meets Reinforcement Learning pi-flow: Policy-based few- step generation via imitation distillation.arXiv preprint arXiv:2510.14974, 2025

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.789550Z

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Observation 8a09de47-3500-4297-b64b-a42980b220fa · outbound

This paper cites ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation.

Distribution Matching Distillation Meets Reinforcement Learning ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.795407Z

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Observation cf63081e-c45a-48d6-b340-8fce38efc413 · outbound

This paper cites Sana-sprint: One-step diffusion with continuous-time con- sistency distillation.arXiv preprint arXiv:2503.09641, 2025.

Distribution Matching Distillation Meets Reinforcement Learning Sana-sprint: One-step diffusion with continuous-time con- sistency distillation.arXiv preprint arXiv:2503.09641, 2025

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.804934Z

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Observation 9467881b-8c9d-4902-afa9-618b7e033fcd · outbound

This paper cites Pose: Phased one-step adversarial equilibrium for video diffusion models.arXiv preprint arXiv:2508.21019, 2025.

Distribution Matching Distillation Meets Reinforcement Learning Pose: Phased one-step adversarial equilibrium for video diffusion models.arXiv preprint arXiv:2508.21019, 2025

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.810665Z

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Observation 1c23ba77-79fd-4d8d-8aa2-cb1052879c21 · outbound

This paper cites text-to-image-2m.https:// huggingface.co/datasets/jackyhate/text- to-image-2M, 2024.

Distribution Matching Distillation Meets Reinforcement Learning text-to-image-2m.https:// huggingface.co/datasets/jackyhate/text- to-image-2M, 2024

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.820997Z

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Observation 44949b83-ed66-4956-a70f-8864536ed362 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

Distribution Matching Distillation Meets Reinforcement Learning Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.830484Z

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Observation 18b74d1d-8de6-4b06-b7e8-7f527c47be91 · outbound

This paper cites Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Models.

Distribution Matching Distillation Meets Reinforcement Learning Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.837698Z

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Observation 26b87f69-e1cc-4119-bf1a-d8a30a22a80b · outbound

This paper cites Data Filtering Networks.

Distribution Matching Distillation Meets Reinforcement Learning Data Filtering Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.845089Z

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Observation 76f44d17-41c4-4db3-9c4c-640b10ef85b8 · outbound

This paper cites One Step Diffusion via Shortcut Models.

Distribution Matching Distillation Meets Reinforcement Learning One Step Diffusion via Shortcut Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.852308Z

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Observation 0d76923a-2112-419d-b18a-a24f4d33f798 · outbound

This paper cites Geneval: An object-focused framework for evaluating text- to-image alignment.Advances in Neural Information Pro- cessing Systems, 36:52132–52152, 2023.

Distribution Matching Distillation Meets Reinforcement Learning Geneval: An object-focused framework for evaluating text- to-image alignment.Advances in Neural Information Pro- cessing Systems, 36:52132–52152, 2023

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.860135Z

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Observation cfd719b8-aaa9-4cbb-af52-9ad674cf6ae1 · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27, 2014.

Distribution Matching Distillation Meets Reinforcement Learning Generative adversarial nets.Advances in neural information processing systems, 27, 2014

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.869063Z

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Observation ef36c053-a2a5-465b-8232-01b5af07318c · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

Distribution Matching Distillation Meets Reinforcement Learning CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.877346Z

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Observation 1821a628-3445-4046-99bf-c988a67efee1 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

Distribution Matching Distillation Meets Reinforcement Learning Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.886710Z

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Observation 18e491f7-f0c5-4ca3-8fde-c7d6ea20ec50 · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

Distribution Matching Distillation Meets Reinforcement Learning ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.896707Z

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Observation 0e9a846b-5365-4efc-b06b-b4ac67adfe54 · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.Ad- vances in neural information processing systems, 36:36652– 36663, 2023.

Distribution Matching Distillation Meets Reinforcement Learning Pick-a-pic: An open dataset of user preferences for text-to-image generation.Ad- vances in neural information processing systems, 36:36652– 36663, 2023

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.903896Z

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Observation 3af2f59c-50b7-47b8-b1c9-f3ec39f6eaa0 · outbound

This paper cites Flux.https://github.com/ black-forest-labs/flux, 2024.

Distribution Matching Distillation Meets Reinforcement Learning Flux.https://github.com/ black-forest-labs/flux, 2024

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.909650Z

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Observation f1b0a961-8a5b-43f2-b01a-fcad2b18b6ef · outbound

This paper cites AnimateDiff-Lightning: Cross-Model Diffusion Distillation.

Distribution Matching Distillation Meets Reinforcement Learning AnimateDiff-Lightning: Cross-Model Diffusion Distillation

Reference 22

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Observation 09f5a319-69d2-429b-9e7e-374b68995c52 · outbound

This paper cites SDXL-Lightning: Progressive Adversarial Diffusion Distillation.

Distribution Matching Distillation Meets Reinforcement Learning SDXL-Lightning: Progressive Adversarial Diffusion Distillation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:19.920882Z

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Observation 961777a9-85c2-4915-84e7-dcb40c54f6e6 · outbound

This paper cites Diffusion adversarial post-training for one-step video generation.arXiv preprint arXiv:2501.08316,.

Distribution Matching Distillation Meets Reinforcement Learning Diffusion adversarial post-training for one-step video generation.arXiv preprint arXiv:2501.08316,

Reference 24

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Observation feef3afc-690f-48d1-baec-d0221d63256b · outbound

This paper cites Autoregressive adversarial post-training for real-time inter- active video generation.arXiv preprint arXiv:2506.09350,.

Distribution Matching Distillation Meets Reinforcement Learning Autoregressive adversarial post-training for real-time inter- active video generation.arXiv preprint arXiv:2506.09350,

Reference 25

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Observation 79617fef-2525-4961-84a2-7cd9efd79ce2 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

Distribution Matching Distillation Meets Reinforcement Learning Flow-GRPO: Training Flow Matching Models via Online RL

Reference 26

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Observation 8bf413ab-4851-4658-9666-f65800f0d7e4 · outbound

This paper cites Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models.

Distribution Matching Distillation Meets Reinforcement Learning Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models

Reference 27

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Observation d7e78a72-bded-4fd0-81ee-87ab99d97577 · outbound

This paper cites Adversarial Distribution Matching for Diffusion Distillation Towards Efficient Image and Video Synthesis.

Distribution Matching Distillation Meets Reinforcement Learning Adversarial Distribution Matching for Diffusion Distillation Towards Efficient Image and Video Synthesis

Reference 28

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Observation 1cc19e15-40d9-42e8-8f39-1418f0ce5243 · outbound

This paper cites Hyper-bagel: A unified acceleration framework for multimodal understand- ing and generation.arXiv preprint arXiv:2509.18824, 2025.

Distribution Matching Distillation Meets Reinforcement Learning Hyper-bagel: A unified acceleration framework for multimodal understand- ing and generation.arXiv preprint arXiv:2509.18824, 2025

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Observation 01cc46db-9795-4e5e-bd5c-57e859d89f6c · outbound

This paper cites Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed.

Distribution Matching Distillation Meets Reinforcement Learning Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed

Reference 30

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Observation bb44aaea-1586-4361-85d8-44c568f5b3eb · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

Distribution Matching Distillation Meets Reinforcement Learning Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

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Observation 55d69eb2-95a2-457d-a1e9-d8abed87c519 · outbound

This paper cites Diff-Instruct++: Training One-step Text-to-image Generator Model to Align with Human Preferences.

Distribution Matching Distillation Meets Reinforcement Learning Diff-Instruct++: Training One-step Text-to-image Generator Model to Align with Human Preferences

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Observation 23dffe9f-3b91-4ef8-ba76-a7916a0839f9 · outbound

This paper cites Diff-instruct: A universal approach for transferring knowledge from pre-trained diffu- sion models.Advances in Neural Information Processing Systems, 36:76525–76546, 2023.

Distribution Matching Distillation Meets Reinforcement Learning Diff-instruct: A universal approach for transferring knowledge from pre-trained diffu- sion models.Advances in Neural Information Processing Systems, 36:76525–76546, 2023

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Observation 51dff4a3-666f-4617-ac94-06e83d94b4ef · outbound

This paper cites Learning Few-Step Diffusion Models by Trajectory Distribution Matching.

Distribution Matching Distillation Meets Reinforcement Learning Learning Few-Step Diffusion Models by Trajectory Distribution Matching

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Observation d58dc18d-2995-4bb3-b831-d1a7d9c11dc1 · outbound

This paper cites Which training methods for gans do actually converge? In International conference on machine learning, pages 3481–.

Distribution Matching Distillation Meets Reinforcement Learning Which training methods for gans do actually converge? In International conference on machine learning, pages 3481–

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Observation 17dea0ba-fa13-499b-b404-28ecce48bd86 · outbound

This paper cites Scalable diffusion models with transformers.

Distribution Matching Distillation Meets Reinforcement Learning Scalable diffusion models with transformers

Reference 36

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Observation 410eb1d7-c2f4-405e-a31d-8646df0ea20f · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Distribution Matching Distillation Meets Reinforcement Learning SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

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Observation 53838aa5-0cb0-46a2-b6bc-5c2b9d8738c5 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Distribution Matching Distillation Meets Reinforcement Learning DreamFusion: Text-to-3D using 2D Diffusion

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Observation 27886d84-cbfe-4079-8920-ccd470257e0e · outbound

This paper cites Lumina-Image 2.0: A Unified and Efficient Image Generative Framework.

Distribution Matching Distillation Meets Reinforcement Learning Lumina-Image 2.0: A Unified and Efficient Image Generative Framework

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Observation 9f03cb80-96d8-4bd4-b8ac-d288b2d50aa8 · outbound

This paper cites Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis.

Distribution Matching Distillation Meets Reinforcement Learning Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

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Observation 072b250a-3797-4a03-8921-830191ed93c2 · outbound

This paper cites Stabilizing training of generative adver- sarial networks through regularization.Advances in neural information processing systems, 30, 2017.

Distribution Matching Distillation Meets Reinforcement Learning Stabilizing training of generative adver- sarial networks through regularization.Advances in neural information processing systems, 30, 2017

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Observation f48d0165-ec3e-4b63-bf70-02fec5948dd2 · outbound

This paper cites Improved techniques for training gans.Advances in neural information processing systems, 29, 2016.

Distribution Matching Distillation Meets Reinforcement Learning Improved techniques for training gans.Advances in neural information processing systems, 29, 2016

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Observation 18a95fbb-d2f8-4113-948f-5b2872a0a897 · outbound

This paper cites Fast high- resolution image synthesis with latent adversarial diffusion distillation.

Distribution Matching Distillation Meets Reinforcement Learning Fast high- resolution image synthesis with latent adversarial diffusion distillation

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Observation 91e6c4f8-3fbb-4f0f-9e00-cd3dfa9b85ba · outbound

This paper cites Adversarial diffusion distillation.

Distribution Matching Distillation Meets Reinforcement Learning Adversarial diffusion distillation

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Observation 3fe50557-8a4b-49e7-bce0-7da90362d206 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294, 2022.

Distribution Matching Distillation Meets Reinforcement Learning Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294, 2022

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Observation 1654f7f6-7acc-486b-9b31-20e2a1cd837d · outbound

This paper cites Seedream 4.0: Toward Next-generation Multimodal Image Generation.

Distribution Matching Distillation Meets Reinforcement Learning Seedream 4.0: Toward Next-generation Multimodal Image Generation

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Observation 36adf26e-5a56-4acb-b6b1-11c20e671a27 · outbound

This paper cites Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference.

Distribution Matching Distillation Meets Reinforcement Learning Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference

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Observation a0323708-dc67-45a2-99c3-d34e1f51e0ee · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Distribution Matching Distillation Meets Reinforcement Learning Score-Based Generative Modeling through Stochastic Differential Equations

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Observation c81ea765-ef6b-477a-a082-dd27135b2b35 · outbound

This paper cites Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer.

Distribution Matching Distillation Meets Reinforcement Learning Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

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Observation fdef03e5-fa4d-4172-8463-3d64eddd5455 · outbound

This paper cites Diffusion model align- ment using direct preference optimization.

Distribution Matching Distillation Meets Reinforcement Learning Diffusion model align- ment using direct preference optimization

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Observation 0a4becdf-6367-470d-8fc0-5f9114ee0490 · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.Advances in neural information processing systems, 36: 8406–8441, 2023.

Distribution Matching Distillation Meets Reinforcement Learning Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.Advances in neural information processing systems, 36: 8406–8441, 2023

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Observation 5bc90bef-5c59-4c41-accd-9ced908fd7a5 · outbound

This paper cites RewardDance: Reward Scaling in Visual Generation.

Distribution Matching Distillation Meets Reinforcement Learning RewardDance: Reward Scaling in Visual Generation

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Observation d02de762-a555-4f10-9f5b-13ca02f9bf7d · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

Distribution Matching Distillation Meets Reinforcement Learning Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

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Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.117993Z

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Observation fb7b317b-6a55-4031-bf0b-51fc95f01c8b · outbound

This paper cites Deep reward supervisions for tuning text-to-image diffusion models.

Distribution Matching Distillation Meets Reinforcement Learning Deep reward supervisions for tuning text-to-image diffusion models

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Unavailable: canonical work link unavailable.

Observation 20463ef9-4128-4eba-8f20-7984d20c874d · outbound

This paper cites Imagere- ward: Learning and evaluating human preferences for text- to-image generation.Advances in Neural Information Pro- cessing Systems, 36:15903–15935, 2023.

Distribution Matching Distillation Meets Reinforcement Learning Imagere- ward: Learning and evaluating human preferences for text- to-image generation.Advances in Neural Information Pro- cessing Systems, 36:15903–15935, 2023

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.131502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f77f0e36-8ca9-41cb-9492-9db0f8cbf27d · outbound

This paper cites One-step Diffusion Models with $f$-Divergence Distribution Matching.

Distribution Matching Distillation Meets Reinforcement Learning One-step Diffusion Models with $f$-Divergence Distribution Matching

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.142079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3444eb43-3312-41bc-bf04-ee2f35ca7e65 · outbound

This paper cites DanceGRPO: Unleashing GRPO on Visual Generation.

Distribution Matching Distillation Meets Reinforcement Learning DanceGRPO: Unleashing GRPO on Visual Generation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.147853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e96d7ca-23a8-403b-aba6-7eb8f27626b5 · outbound

This paper cites Magic 1-For-1: Generating One Minute Video Clips within One Minute.

Distribution Matching Distillation Meets Reinforcement Learning Magic 1-For-1: Generating One Minute Video Clips within One Minute

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.154969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbcc9f2a-dd2d-4ccf-83fc-ada5efc57ebe · outbound

This paper cites Im- proved distribution matching distillation for fast image syn- thesis.Advances in neural information processing systems, 37:47455–47487, 2024.

Distribution Matching Distillation Meets Reinforcement Learning Im- proved distribution matching distillation for fast image syn- thesis.Advances in neural information processing systems, 37:47455–47487, 2024

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.162833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 448eff7a-e3a0-44c7-a549-46d4c6ee225b · outbound

This paper cites One-step diffusion with distribution matching distillation.

Distribution Matching Distillation Meets Reinforcement Learning One-step diffusion with distribution matching distillation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.169024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97643b2b-902c-43c7-b2ef-d8b2e5332d3c · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Distribution Matching Distillation Meets Reinforcement Learning The unreasonable effectiveness of deep features as a perceptual metric

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.176427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c636e63-eba1-49c4-8dfb-bd9323d89a76 · outbound

This paper cites Prospect: Prompt spectrum for attribute-aware personalization of diffusion models.ACM Transactions on Graphics (TOG), 42(6):1–14, 2023.

Distribution Matching Distillation Meets Reinforcement Learning Prospect: Prompt spectrum for attribute-aware personalization of diffusion models.ACM Transactions on Graphics (TOG), 42(6):1–14, 2023

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.184771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11c0d711-fe0c-4550-b88d-0e52a56bce28 · outbound

This paper cites Towards Highly Realistic Artistic Style Transfer via Stable Diffusion with Step-aware and Layer-aware Prompt.

Distribution Matching Distillation Meets Reinforcement Learning Towards Highly Realistic Artistic Style Transfer via Stable Diffusion with Step-aware and Layer-aware Prompt

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.189788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7d23dc2-645b-4b05-ac6f-80b4a213fee2 · outbound

This paper cites Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency.

Distribution Matching Distillation Meets Reinforcement Learning Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T21:47:20.196175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c53013c3-3f50-4d57-a96c-e78bfeb2580e · inbound

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer cites this paper.

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer Distribution Matching Distillation Meets Reinforcement Learning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6bb10234-dd0d-4a45-b7b6-9b94bdb865e0 · inbound

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer cites this paper.

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer Distribution Matching Distillation Meets Reinforcement Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T19:47:32.038741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73cc5f58-33af-4aca-b1f5-27cb1ebd8d40 · inbound

Optimizing Few-Step Generation with Adaptive Matching Distillation cites this paper.

Optimizing Few-Step Generation with Adaptive Matching Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T03:42:45.145549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b91bd38c-f6b7-4b12-8722-32bace99f490 · inbound

Cross-Resolution Distribution Matching for Diffusion Distillation cites this paper.

Cross-Resolution Distribution Matching for Diffusion Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-15T14:00:06.859472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a38a6f9-5314-4aff-ab43-b6c529b868ed · inbound

1.x-Distill: Breaking the Diversity, Quality, and Efficiency Barrier in Distribution Matching Distillation cites this paper.

1.x-Distill: Breaking the Diversity, Quality, and Efficiency Barrier in Distribution Matching Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7849e469-4715-4e30-9de5-6c4ca3839ea4 · inbound

Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning cites this paper.

Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning Distribution Matching Distillation Meets Reinforcement Learning

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0d314805-75f4-47c8-80f3-63955249e583 · inbound

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation cites this paper.

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c81b9f58-2f74-4cd7-84b3-c3bb2b523547 · inbound

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE cites this paper.

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE Distribution Matching Distillation Meets Reinforcement Learning

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1f961743-321a-46a9-a698-e0be6067dd07 · inbound

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation cites this paper.

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 95a699f1-42b5-48f6-8ec5-cb7da0e9f667 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Distribution Matching Distillation Meets Reinforcement Learning

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fb23a55b-d015-4a34-82b3-8930af542a2f · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Distribution Matching Distillation Meets Reinforcement Learning

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f1d6fd0a-9953-4bdf-b31e-9c90a1261647 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Distribution Matching Distillation Meets Reinforcement Learning

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation da224802-c59c-4439-b115-ec088e0d8830 · inbound

Continuous-Time Distribution Matching for Few-Step Diffusion Distillation cites this paper.

Continuous-Time Distribution Matching for Few-Step Diffusion Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4acc7b94-e7b3-43e4-9427-4f1b47590778 · inbound

FlashMol: High-Quality Molecule Generation in as Few as Four Steps cites this paper.

FlashMol: High-Quality Molecule Generation in as Few as Four Steps Distribution Matching Distillation Meets Reinforcement Learning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f27e6696-923a-45e1-aa94-b0f5a18dff75 · inbound

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation cites this paper.

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation da5a8475-7cad-4ed4-8ae1-3d500a559206 · inbound

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation cites this paper.

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb9e8483-e177-4618-bdb2-6f61fb1cb966 · inbound

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation cites this paper.

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2a5092fd-61bc-4457-a64d-70b8a295913a · inbound

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation cites this paper.

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cc6f102d-814a-4526-8697-e2006f36e3ed · inbound

Efficient Image Synthesis with Sphere Latent Encoder cites this paper.

Efficient Image Synthesis with Sphere Latent Encoder Distribution Matching Distillation Meets Reinforcement Learning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a7696072-52c2-4ccd-8f09-e8f2a9197c5b · inbound

Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models cites this paper.

Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models Distribution Matching Distillation Meets Reinforcement Learning

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5fc4877f-5b53-405a-bece-3852aa9de233 · inbound

ERNIE-Image Technical Report cites this paper.

ERNIE-Image Technical Report Distribution Matching Distillation Meets Reinforcement Learning

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9422a8a2-623b-4d29-9f7c-6508d7a7ece6 · inbound

CollectionLoRA: Collecting 50 Effects in 1 LoRA via Multi-Teacher On-Policy Distillation cites this paper.

CollectionLoRA: Collecting 50 Effects in 1 LoRA via Multi-Teacher On-Policy Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 522b3761-f1c0-47aa-b4c7-a721aab6b924 · inbound

Reinforcing Few-step Generators via Reward-Tilted Distribution Matching cites this paper.

Reinforcing Few-step Generators via Reward-Tilted Distribution Matching Distribution Matching Distillation Meets Reinforcement Learning

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1a3886f7-92f4-4276-ac16-4a110bd9de58 · inbound

Drifting Preference Optimization for One-Step Generative Models cites this paper.

Drifting Preference Optimization for One-Step Generative Models Distribution Matching Distillation Meets Reinforcement Learning

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 128885d4-6795-4eb3-892b-65d062cfa678 · inbound

Qwen-Image-Flash: Beyond Objective Design cites this paper.

Qwen-Image-Flash: Beyond Objective Design Distribution Matching Distillation Meets Reinforcement Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a3ca6ace-cbf0-4515-b31b-44ad7214715f · inbound

World Model Self-Distillation: Training World Models to Solve General Tasks cites this paper.

World Model Self-Distillation: Training World Models to Solve General Tasks Distribution Matching Distillation Meets Reinforcement Learning

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3ae41e45-4829-4ba6-b92f-732c231d059c · inbound

High-Fidelity Two-Step Image Generation via Teacher-Aligned End-to-End Distillation cites this paper.

High-Fidelity Two-Step Image Generation via Teacher-Aligned End-to-End Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f0589c07-6fca-4f94-b7d1-c0db0110eec9 · inbound

A Test-time Actor-Critic Approach to News Images Generation cites this paper.

A Test-time Actor-Critic Approach to News Images Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b3e499a0-4b78-4e42-9fae-d6151a74b37c · inbound

CoDMD: Copula-aware Distribution Matching Distillation for Fast Video Generation cites this paper.

CoDMD: Copula-aware Distribution Matching Distillation for Fast Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1ed7f70e-6fdd-499b-952a-e394c687545f · inbound

Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models cites this paper.

Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models Distribution Matching Distillation Meets Reinforcement Learning

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 32f72587-5a5e-4c0d-89fa-f9eecd2754cd · inbound

Monocular Avatar Reconstruction via Cascaded Diffusion Priors and UV-Space Differentiable Shading cites this paper.

Monocular Avatar Reconstruction via Cascaded Diffusion Priors and UV-Space Differentiable Shading Distribution Matching Distillation Meets Reinforcement Learning

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:14.617836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 304058dd-68e5-471e-9b7f-c42064167c4c · inbound

Reward Lightning: Fast Video Generation via Homologous Preference Distillation cites this paper.

Reward Lightning: Fast Video Generation via Homologous Preference Distillation Distribution Matching Distillation Meets Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-11T22:44:24.796514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cc6b38d-e839-41c9-ad36-ef19c5251285 · inbound

Twins: Learn to Predict Unified Representations with Focal Loss cites this paper.

Twins: Learn to Predict Unified Representations with Focal Loss Distribution Matching Distillation Meets Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T04:29:43.796534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6050ca8-cdea-45c3-839a-22ec12bcdf39 · inbound

ScaleResfusion: Residual Rectified Flow based on Residual Vector Field cites this paper.

ScaleResfusion: Residual Rectified Flow based on Residual Vector Field Distribution Matching Distillation Meets Reinforcement Learning

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-01T02:58:31.990096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 473df447-f9ed-4b85-bac9-148502b865f4 · inbound

RL-Native Distillation: Exploiting Scored Trajectories for Few-Step Image Generation cites this paper.

RL-Native Distillation: Exploiting Scored Trajectories for Few-Step Image Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T21:17:25.986375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dfd2f3b-42a5-4877-8c96-c057aa24285d · inbound

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation cites this paper.

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation Distribution Matching Distillation Meets Reinforcement Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T13:43:34.781498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.